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快速循环系统建模,以支持全系统实施过程中基于证据的决策。

Rapid-cycle systems modeling to support evidence-informed decision-making during system-wide implementation.

作者信息

Sheldrick R Christopher, Cruden Gracelyn, Schaefer Ana J, Mackie Thomas I

机构信息

Department of Health Law, Policy and Management, School of Public Health, Boston University, One Silber Way, Boston, MA, USA.

Oregon Social Learning Center, 10 Shelton McMurphey Blvd, Eugene, OR, USA.

出版信息

Implement Sci Commun. 2021 Oct 9;2(1):116. doi: 10.1186/s43058-021-00218-6.

DOI:10.1186/s43058-021-00218-6
PMID:34627399
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8502394/
Abstract

BACKGROUND

To "model and simulate change" is an accepted strategy to support implementation at scale. Much like a power analysis can inform decisions about study design, simulation models offer an analytic strategy to synthesize evidence that informs decisions regarding implementation of evidence-based interventions. However, simulation modeling is under-utilized in implementation science. To realize the potential of simulation modeling as an implementation strategy, additional methods are required to assist stakeholders to use models to examine underlying assumptions, consider alternative strategies, and anticipate downstream consequences of implementation. To this end, we propose Rapid-cycle Systems Modeling (RCSM)-a form of group modeling designed to promote engagement with evidence to support implementation. To demonstrate its utility, we provide an illustrative case study with mid-level administrators developing system-wide interventions that aim to identify and treat trauma among children entering foster care.

METHODS

RCSM is an iterative method that includes three steps per cycle: (1) identify and prioritize stakeholder questions, (2) develop or refine a simulation model, and (3) engage in dialogue regarding model relevance, insights, and utility for implementation. For the case study, 31 key informants were engaged in step 1, a prior simulation model was adapted for step 2, and six member-checking group interviews (n = 16) were conducted for step 3.

RESULTS

Step 1 engaged qualitative methods to identify and prioritize stakeholder questions, specifically identifying a set of inter-related decisions to promote implementing trauma-informed screening. In step 2, the research team created a presentation to communicate key findings from the simulation model that addressed decisions about programmatic reach, optimal screening thresholds to balance demand for treatment with supply, capacity to start-up and sustain screening, and availability of downstream capacity to provide treatment for those with indicated need. In step 3, member-checking group interviews with stakeholders documented the relevance of the model results to implementation decisions, insight regarding opportunities to improve system performance, and potential to inform conversations regarding anticipated implications of implementation choices.

CONCLUSIONS

By embedding simulation modeling in a process of stakeholder engagement, RCSM offers guidance to realize the potential of modeling not only as an analytic strategy, but also as an implementation strategy.

摘要

背景

“建模与模拟变革”是一种被认可的大规模支持实施的策略。就像功效分析可为研究设计决策提供依据一样,模拟模型提供了一种分析策略,用于综合证据,为基于证据的干预措施实施决策提供信息。然而,模拟建模在实施科学中未得到充分利用。为了实现模拟建模作为一种实施策略的潜力,需要额外的方法来帮助利益相关者使用模型来检验潜在假设、考虑替代策略以及预测实施的下游后果。为此,我们提出快速循环系统建模(RCSM)——一种旨在促进与证据互动以支持实施的群体建模形式。为证明其效用,我们提供了一个案例研究,涉及中级管理人员制定全系统干预措施,旨在识别和治疗进入寄养机构的儿童中的创伤情况。

方法

RCSM是一种迭代方法,每个循环包括三个步骤:(1)识别利益相关者问题并确定优先级;(2)开发或完善模拟模型;(3)就模型对实施的相关性、见解和效用进行对话。对于该案例研究,31名关键信息提供者参与了第一步,第二步采用了一个先前的模拟模型并进行了调整,第三步进行了六次成员核对小组访谈(n = 16)。

结果

第一步采用定性方法识别利益相关者问题并确定优先级,具体确定了一组相互关联的决策,以促进实施创伤知情筛查。在第二步中,研究团队创建了一个演示文稿,以传达模拟模型的关键发现,这些发现涉及项目覆盖范围、平衡治疗需求与供应的最佳筛查阈值、启动和维持筛查的能力以及为有需求者提供治疗的下游能力可用性等决策。在第三步中,与利益相关者进行的成员核对小组访谈记录了模型结果与实施决策的相关性、关于改善系统性能机会的见解以及为有关实施选择预期影响的对话提供信息的潜力。

结论

通过将模拟建模嵌入利益相关者参与过程中,RCSM不仅为实现建模作为一种分析策略的潜力提供指导,也为实现其作为一种实施策略的潜力提供指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db0d/8502394/a8f8a40a6289/43058_2021_218_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db0d/8502394/e6b5bfbf387e/43058_2021_218_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db0d/8502394/a8f8a40a6289/43058_2021_218_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db0d/8502394/e6b5bfbf387e/43058_2021_218_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db0d/8502394/a8f8a40a6289/43058_2021_218_Fig2_HTML.jpg

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